Recently you may have heard the phrase "Expected goals" being used when it comes to discussions around a football game or a team's performances in general.
It's certainly gone from something discussed primarily on the fringes of data-focused analysis into a more mainstream topic in recent months but what is it all about and is it useful to bettors aiming to assess the opportunities available in the market at any given point?
What is Expected Goals (xG)?
Expected Goals (xG) is a metric that quantitatively assesses the quality of each shot taken during a game. This metric allows a more rounded view of the goal scoring opportunities that were created. Players, fans and managers can cite being “unlucky” during any particular contest but how are they measuring the amount of "luck" their side received?
Firstly, how many shots a team takes at goal during a match can only tell you so much about how they've performed. Indeed, it can be the case that a side who create fewer chances that, crucially, are of a higher quality, win the match despite looking second best on the basic shot count metric.
Not all shots are equal in terms of how likely they are to result in a goal. In fact, there are many factors which determine how they're rated when it comes to Expected Goals.
How far out was the player when they took the shot? Was it a favourable angle in relation to the goal? Was it a header? All of these elements and several more have an impact on how likely it is that the effort in question ends up in the back of the net.
At the time of writing, Opta have catalogued over 300,000 shots from their database and adjusted them for different leagues in order to come up with an xG model that determines the value of any given shot and rates them on a numerical basis.
For example, if a shot is measured at 0.1 xG, this equates to one in every 10 efforts resulting in a goal. For more information on how Expected Goals is calculated by Opta, check out their blog on the subject or this YouTube video.
How does xG relate to betting?
Analysing form is a key part to betting on football for a large proportion of punters and there are dozens of different metrics that are available in this area. While there is no magic formula to this process, tools such as xG can help create a more rounded view of a team's recent run or a specific performance in isolation.
While every bettor will have their own methodology in assessing the opportunities available in the market, xG provides an interesting narrative. Variance and understanding it is a key part of betting, especially when it comes to winning or losing runs.
The same is true of the variances in a sides' performances, how much value should you put on a game where the data suggested that the result was in fact a significant outlier in terms of what you'd expect were to be played 100 or even 1000 times over?
It might not be the only reason for opposing or backing a certain team, or indeed any other outcome, but xG allows bettors to get a handle on the quality of chances a team have created over a set period. That can certainly be useful when aiming to make a judgement about future performances, especially in the face of raw shot data which might not tell the whole story when taken in isolation.
Here are a couple of recent examples of the application of xG from the Premier League campaign so far.
Harry Kane in August
He may have been the top goal scorer in each of the previous two Premier League seasons but Harry Kane has never scored a top-flight goal in the month of August. However, this term Kane's xG was quite high (2.9) during that period, suggesting he was pretty unlucky during the first few weeks of the campaign.
With that in mind, it's no surprise that the England international has been able to play catch up with his rivals in the months in emphatic fashion following this slow start. In stark contrast to August, Kane scored six non-penalty goals in September from an xG of 2.1 and since then his goal tally has largely fallen in line with his xG as he tops the scoring charts once again.
Crystal Palace's contrasting fortunes
To say the Premier League campaign began poorly for Crystal Palace is an understatement. It took the Eagles until October 14 2017 to score their first league goal of the campaign and by then Frank de Boer had already paid the price for a string of four top flight defeats in a row.
This lack of potency in front of goal had plenty of people, including the bookmakers, expecting Palace to drop down to the Championship.
However, the data suggests that the quality of chances created should have yielded 8.1 goals on average in the time it took the London club to net their first one. On the other side of the equation, the same metric revealed that they were slightly unlucky on the defensive side, conceding 17 times compared with 13.8 xG conceded.
Since then though, Palace have seen their results largely come back into line with xG tallies (20 goals scored from 22.4 xG and 16 conceded from 14.5 xG against), the results have followed suit and the early season strugglers now sit much more comfortably in 14th with 22 points to their name.